Senior Advanced Analyst, Fraud & Safety Investigations

Description

Airbnb was born in 2007 when two Hosts welcomed three guests to their San Francisco home, and has since grown to over 4 million Hosts who have welcomed more than 1 billion guest arrivals in almost every country across the globe. Every day, Hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.

The Analytics Centre of Excellence (ACOE) at Airbnb, based in India, is a hub of knowledge and expertise that aims to provide data-driven decision-making, enabling Airbnb's business goals. The ACOE's vision is to build a world-class analytics organization that provides scalable analytics. We work with various business functions such as payments, trust, digital, customer support, hosting, sales, social, compliance, risk, platforms and partnership & economics.

The ACOE's delivery framework is designed to provide relevant and contextual insights for data-driven decisions. This includes a one-stop solution for metrics, dashboards driving actionable insights, optimization of performance, measuring pre/post feature impact, sizing the ROI of opportunities, prioritization of opportunities, anomaly-driven alerting mechanisms, root cause analysis of metric deviation, and exploratory hypothesis testing.

The Community You Will Join:

We are looking for a senior advanced analyst in our India Analytics team who works with the Fraud & Safety Delivery team. The analyst must have functional expertise in building analytical solutions and be a trusted partner to product teams and business leaders, across marketplace teams through providing insights, recommendations, and enabling data driven decisions. This role will sit under the Advanced Analytics family and support Product and Business leaders within our Fraud & Safety organization.

The Difference You Will Make:

• Work with technical and business teams to develop robust insights, create data narratives and leverage Airbnb’s rich data to define metrics.
• Build advanced analytical capabilities and tools, passionate about solving complex problems with data; adding a new perspective to existing solutions and making business decisions based on careful and thoughtful analysis.
• Leverage Airbnb’s state-of-art machine learning infrastructure, and other central data science tools to build and collaborate with a strong team of engineers, product managers, designers and operation agents to achieve shared, cross-functional goals.
• You have a strong sense of urgency for and commitment to Airbnb’s mission of belonging.
• Develop a deep understanding of how guests and hosts interact with our Fraud & Safety frictions and how we can manage our risk while meeting our regulatory compliance requirements, through structured and unstructured data sources.

A Typical Day:

• Execute projects with regular direction; Set a roadmap for projects up to a quarter ahead providing constant updates to business stakeholders, analytics management and deliver against agreed timelines.
• Ensure the availability of data quality and data integrity for analysis and reporting, by blending external and internal data, working closely with global operations and India analytics functions.
• Perform data modeling for the various entities involved in Airbnb including customers, hosts, cases, agents, and others using modern data modeling tools and frameworks to provide the analytical foundation.
• Execute ad-hoc reporting, data investigations, and root cause analysis into various operational areas including policy incubation, enforcement efficacy, prevalence, efficiency, agent tooling, agent staffing & optimization, and agent quality & efficiency to identify and solve for operational bottlenecks and inefficiencies.
• Devise business metric frameworks and optimization models to make optimal business decisions that support arguments for Airbnb’s product, operations and policy issues
• Influence data-driven decisions across global sites and business verticals in day-to-day via business reviews, self-serve portal, planning scorecards, and impact analyses among others.
• Experiment with new Airbnb policy / product features to help deter and mitigate risk
• Influence machine learning models in partnership with DS / Engg teams to automate policy enforcement decisions, while enqueueing the most complex cases for manual review by agents